1. Field of Invention
The present invention pertains to the field of Positron Emission Tomography (PET). More particularly, this invention is directed to a dedicated memory device for extremely flexible and general purpose support of on-line event-by-event normalization, real-time physiological gating, unity (+/−) histogramming, and weighted histogramming.
2. Description of the Related Art
Various techniques are used for medical imaging. Positron emission tomography (PET) is one of several popular methods in radiology because of its ability to non-invasively study physiological processes and structures within the body. PET is a nuclear imaging technique used in the medical field to assist in the diagnosis of diseases. PET allows the physician to examine the whole patient at once by producing pictures of many functions of the human body unobtainable by other imaging techniques. In this regard, PET displays images of how the body works (physiology or function) instead of simply how it looks. PET is considered the most sensitive, and exhibits the greatest quantification accuracy, of any nuclear medicine imaging instrument available at the present time. Applications requiring this sensitivity and accuracy include those in the fields of oncology, cardiology, and neurology.
In PET, short-lived positron-emitting isotopes, referred to as radiopharmaceuticals, are injected into a patient. When these radioactive drugs are administered to a patient, they distribute within the body according to the physiologic pathways associated with their stable counterparts. As the radiopharmaceutical isotopes decay in the body, they discharge positively charged particles called positrons. Upon discharge, the positrons encounter electrons, and both are annihilated. As a result of each annihilation event, gamma rays are generated in the form of a pair of diametrically opposed photons approximately 180 degrees (angular) apart. After the PET scanner detects these annihilation “event pairs” over a period of time, the isotope distribution in a cross section of the body is reconstructed. These events are mapped within the patient's body, thus allowing for the quantitative measurement of metabolic, biochemical, and functional activity in living tissue. More specifically, PET images (often in conjunction with an assumed physiologic model) are used to evaluate a variety of physiologic parameters such as glucose metabolic rate, cerebral blood flow, tissue viability, oxygen metabolism, and in vivo brain neuron activity.
For the current state-of-the-art in PET, critical technical challenges to data acquisition are frequently encountered. Clinical PET places a demanding burden on the electronic data acquisition architecture, especially when using larger, higher sensitivity detector arrays coupled with demands for high patient throughput. Pure list-mode data acquisition, in which gamma-pair-coincidence event packets are simply stored to disk in the order detected, can have limited acceptance due to either too-slow event-packet collection speeds and/or too-slow post-acquisition processing. The typical resolution for this problem, which is well documented in the literature, has been to perform histogramming (+/− unity to memory) in an on-line manner. For example, projection space “sinograms” are generated during the acquisition while the patient is still in the tomograph. Still, this solution alone shows several limitations when upcoming requirements for modern large-array PET detectors are considered—i.e., requirements such as dynamic studies, continuous bed motion, physiological gating, time-of-flight, and correction for patient motion. In the clinical setting, demands for high-patient throughput combined with these more complex data acquisition modalities result in a critical need for very capable and flexible electronic architectures to support on-line processing of the PET data stream.
One example of a long-axis, high-count-rate PET is described by Wienhard, et al., “The ECAT HRRT: Performance and First Clinical Application of the New High Resolution Research Tomograph,” IEEE Trans. Nucl. Sci., vol. 49, pp. 104-110 (2002). Another example of long-axis, high-count-rate PET is described by Jones, et al., “First Time Measurement of Transaxial Resolution for a New High-Sensitivity PET Prototype Using 5 LSO Panel Detectors,” IEEE NSS/MIC Conf. Rec., 
2002. For an example of work in support of list-mode continuous bed motion in
PET, see Townsend, et al., “Continuous bed motion acquisition for an LSO PET/CT scanner” IEEE NSS/MIC Poster, 2004 Rome. As an example of recent work in support of time-of-flight, refer to the work by Conti, et al., “Implentation of Time-of-Flight on CPS HiRez PET Scanner,” IEEE NSS/MIC Oral Presentation, 2004 Rome. For work in the field of list-mode correction of patient motion, see the article by Fulton, et al., “Event-by-event motion compensation in 3D PET”, IEEE MIC Conf Rec., October 2003.
So as broad progress in PET continues, important challenges must be met in digital electronic architectures to bring these multiple, complex data-acquisition modalities into the clinical world of high-patient throughput. As a basis for progress, note Section VIII from this 1996 article which proposes the use of quad-interleaved DRAM for fast on-line PET histogramming: Jones, et al., “Next generation PET data acquisition architectures,” IEEE MIC Conf Rec., (1996).